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Foster J. Provost

Foster J. Provost

Joined Stern 1999

Leonard N. Stern School of Business
Kaufman Management Center
44 West Fourth Street, 8-86
New York, NY 10012

E-mail fprovost@stern.nyu.edu
Personal website

Biography

FOSTER PROVOST is Professor of Information Systems, Andre Meyer Faculty Fellow, and Director, Fubon Center, Data Analytics & AI, at the Stern School of Business at New York University. He is also Professor of Data Science and former interim Director of the NYU's Center for Data Science. He previously was Editor-in-Chief of the journal Machine Learning and was elected as a founding board member of the International Machine Learning Society. Foster stands out in data science for having made substantial contributions across research, business thought leadership, and practical applications.

Foster's research on data science and machine learning has won many awards, including (among others) the 2017 European Research Paper of the Year, Best Paper awards in the top research venues across three decades, the 2009 INFORMS Design Science Award from the top professional society for operations research, IBM Faculty Awards, and a President’s Award from NYNEX Science and Technology (now Verizon).

For more than 25 years, Prof. Provost has helped leaders in business and government understand how data science, artificial intelligence, and machine learning technologies can add value. His book Data Science for Business is required reading in many of the top business schools, and was listed as one of Fortune Magazine's "must read books for MBAs." He has designed AI/machine learning systems for some of the largest companies in the world and worked with the DoD on the application of AI/machine learning to counter-terrorism.

Foster also has had substantial experience helping to found startups. He was the founding chief scientist for both companies (Media6Degrees and Everyscreen Media) that now form adtech data science powerhouse Dstillery, designing the original machine learning algorithms and building the founding data science teams for both. He also was a coFounder of Detectica, Belgium's Predicube, and most notably, "baby unicorn" Integral Ad Science, which was acquired by Vista Equity Partners this summer for a reported $850M, on the way to an IPO.

Foster is the Former interim Director of the NYU Center for Data Science. He serves on the Scientific Advisory Board for the ISI Foundation, as well as on the NYU Venture Fund Investment Review Board.

Research Interests

  • Integrating humans and AI systems to be better than either alone
  • Mining social network data
  • Privacy-friendly adtech
  • Micro-outsourcing for knowledge discovery and data quality
  • Active & costly data acquisition for modeling
  • Machine learning
  • Behavior profiling

Courses Taught

  • Data Mining, Managerial
  • Data Science for Business Analytics
  • Data Science Research Seminar
  • Introduction to Business Analytics

Academic Background

Ph.D., Computer Science, 1992
University of Pittsburgh

M.S., Computer Science, 1988
University of Pittsburgh

B.S., Physics & Mathematics, 1986
Duquesne University

Awards & Appointments

 
European Research Paper of the Year 2017  
Best Paper Award, ACM SIGKDD 2012, Industry Track  
Best Paper Award, KDD 1997  
IBM Faculty Awards, 2000 & 2001  
Best Paper Award Runner-up, ACM SIGKDD 2008  
The INFORMS Design Science Award, 2009  
Best Paper Award, Information Systems Research (2016)  
2014 NYU/Stern MSBA Best Teacher Award  
Nominated for 2013 and 2014 NYU/Stern Professor of the Year by the MBA student body  
President's Award, NYNEX Science and Technology (now Verizon)  

Selected Publications

D. Chen, S. Fraiberger, R. Moakler & F. Provost (2017)
Enhancing Transparency and Control When Drawing Data-Driven Inferences about Individuals
Big Data

Provost, F., D. Martens, and A. Murray (2015)
Finding Mobile Consumers with a Privacy-Friendly Geo-Similarity Network
Information Systems Research; Best Paper Award; INFORMS President’s Pick.

F. Provost and T. Fawcett (2013)
Data Science and its Relation to Big Data and Data-driven Decision Making
Big Data

Ipeirotis, P., F. Provost, V. Sheng, J. Wang (2013)
Repeated Labeling Using Multiple Noisy Labelers
Data Mining and Knowledge Discovery